This article introduces GeneAgent, an advanced AI agent designed to improve gene-set analysis by reducing factual errors, known as hallucinations, often produced by large language models (LLMs). GeneAgent achieves this by autonomously interacting with various biological databases to verify its own generated outputs, ensuring greater accuracy in functional descriptions of gene sets. The research demonstrates that GeneAgent significantly outperforms conventional LLMs like GPT-4 in generating relevant and comprehensive biological process names and explanations. The system's effectiveness is attributed to its self-verification pipeline and its ability to access and leverage expert-curated domain-specific databases.
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